• Journal of the Korean Statistical Society
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• 제25권1호
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• pp.1-24
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• 1996

In selecting a final tree, Breiman, Friedman, Olshen, and Stone(1984) compare the prediction risks of a pair of tree, where one contains the other, using the standard error of the prediction risk of the larger one. This paper proposes an approach to selection of a final tree by using the standard error of the difference of the prediction risks between a pair of trees rather than the standard error of the larger one. This approach is compared with CART's for simulated data from a simple regression model. Asymptotic results of the approaches are also derived and compared to each other. Both the asymptotic and the simulation results indicate that final trees by CART tend to be smaller than desired.

• 한국기계가공학회지
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• 제11권5호
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• pp.42-47
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• 2012

Construction equipment is heavily loaded during normal operation. In recent years, there is a trend that lower gear noise levels are demanded for drivers to avoid annoyance and fatigue during operation. For articulated hauler's final drive, meshing transmission error(T.E.) is the excitation that leads the tonal noise known as gear whine, and radiated gear whine is also the dominant source of noise in the whole gearbox. This paper presents a method for the analysis of the tooth profile modification, and the prediction of transmission error under the loaded torques for the spur gear pair of the articulated hauler's final drive. And the transmission error, transmission error harmonics and contact stress are also calculated and compared before and after tooth modification under one torque. The simulation result shows that the transmission error and contact stress under the loads can be minimized by the appropriate tooth profile modification.

• ETRI Journal
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• 제46권3호
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• 한국경영과학회지
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• 제30권4호
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• pp.27-43
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• 2005

This paper presents a new hybrid data mining technique using error pattern modeling to improve classification accuracy when the data type of a target variable is binary. The proposed method increases prediction accuracy by combining two different supervised learning methods. That is, the algorithm extracts a subset of training cases that are predicted inconsistently by both methods, and models error patterns from the cases. Based on the error pattern model, the Predictions of two different methods are merged to generate final prediction. The proposed method has been tested using practical 10 data sets. The analysis results show that the performance of proposed method is superior to the existing methods such as artificial neural networks and decision tree induction.

• 산업기술연구
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• 제28권A호
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• pp.11-17
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• 2008

Applicability of hyperbolic settlement prediction method to consolidation settlement in the dredged and reclaimed ground was assessed by analyzing results of centrifuge tests modelling self-weight consolidation of soft marine clay. From literature review about self-weight consolidation of soft marine clays located in southern coast in Korea, constitutive relationships of void ratio - effective stress - permeability and typical self-weight consolidation curves with time were obtained by analyzing centrifuge model experiments. For the condition of surcharge loading, exact solution of consolidation settlement curve obtained by using Terzaghi's consolidation theory was compared with results predicted by the hyperbolic method. It was found to have its own inherent error to predict final consolidation settlement. From results of analyzing thc self-weight consolidation with time by using this method, it predicted relatively well in error range of 0.04~18% for the case of showing the linearity in the relationship between T vs T/S in the stage of consolidation degree of 60~90 %. However, it overestimated the final settlement with large errors if those relation curves were nonlinear.

• 한국정보통신학회논문지
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• 제18권10호
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• pp.2562-2570
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• 2014

단백질의 기능을 유추할 수 있는 중요한 정보중의 하나는 단백질이 존재하는 세포내 위치이다. 최근에는 하나의 단백질이 동시에 존재하는 여러 세포내 위치를 예측하는 연구가 활발하다. 본 논문에서는 단백질이 존재하는 세포내의 다중위치를 예측하기 위해서 레이블 멱집합 방법을 개선한다. 레이블 멱집합 방법으로 분류한 다중위치들을 예측 확률에 따라 결합하여 최종적인 다중레이블로 분류한다. 각 다중위치에 대한 정확한 확률적 기여를 구하기 위하여 쌍별 비교와 오류정정 출력코드를 사용한 다중클래스 확률추정 방법을 적용하였다. 단백질 세포내 위치 예측 실험에 제안한 방법을 적용하여 성능이 향상됨을 보였다.

• 대한토목학회논문집
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• 제6권4호
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• pp.43-52
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• 1986

computer의 활용이 증대됨에 따라 각종 자료의 회귀분석에 최소자승법이 널리 사용되고 있다. computer의 유효자리수에 따른 회귀계수의 불안정성과 표준최소자승법의 문제점을 기술하고, 이를 개선시키는 방안으로 직교함수를 이용한 최소자승법을 사용하였다. 또한 위의 두가지 방법의 결과를 수치검정예를 통하여 비교 분석하였으며 직교함수를 재직교화하여 정밀도를 향상시키는 기법도 다루었다. 적용예로 AR 과정의 적정차수를 결정하는 Akaike의 FPE(final prediction error)를 이용하여 평창관측소의 월유량 시계열의 AR 과정 적정차수를 구하였으며, AR(2)가 적합한 것으로 선정되었다.

• 디지털산업정보학회논문지
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• 제16권3호
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.

• 소성∙가공
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• 제23권7호
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• pp.446-452
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• 2014

In the current study finite element forming analysis is performed to understand the final geometric accuracy limitations for the stamping of an automotive S-rail from four different steel sheets having tensile strengths of 340MPa, 440MPa, 590MPa and 780MPa. Comparisons between the analysis and the experiments for both springback and formability as measured by the amount of edge draw-in and the thickness distribution were conducted. The springback modes were classified according to a scheme proposed in the current investigation and the error was calculated using the normalized root mean square error method. While the analysis results show fairly good agreement with the experimental data for deformation and formability, the simulation accuracy is lower for predicting wall curl, camber and section twist as the UTS of steel sheet increases.

• 한국생산제조학회지
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• 제18권6호
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• pp.681-689
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• 2009

Disk grinding was often applied to deburring process in order to enhance the final product quality. Inherent chamfering capability of the flexible disk grinding process in the early stage was analyzed with respect to various process parameters including workpiece length, wheel speed, depth of cut and feed. Initial chamfered edge defined as arc zone was characterized with local radius of curvature. Averaged radius and arc zone ratio was well evaluated using neural network system. Additional neural network analysis adding workpiece length showed enhance performance in predicting arc zone ratio and curvature radius with reduced error rate. A process condition design parameter was estimated using remaining input and output parameters with the prediction error rate lower than 2.0% depending on the relevant input parameter combination and neural network structure composition.